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Entropy 2012, 14(3), 480-490;

Interval Entropy and Informative Distance

Department of Statistics, Science and Research Branch, Islamic Azad University, Tehran, 14778-93855, Iran
School of Mathematics, Iran University of Science and Technology, Tehran, 16846-13114, Iran
Author to whom correspondence should be addressed.
Received: 20 December 2011 / Revised: 4 February 2012 / Accepted: 7 February 2012 / Published: 2 March 2012
(This article belongs to the Special Issue Concepts of Entropy and Their Applications)
View Full-Text   |   Download PDF [119 KB, uploaded 24 February 2015]


The Shannon interval entropy function as a useful dynamic measure of uncertainty for two sided truncated random variables has been proposed in the literature of reliability. In this paper, we show that interval entropy can uniquely determine the distribution function. Furthermore, we propose a measure of discrepancy between two lifetime distributions at the interval of time in base of Kullback-Leibler discrimination information. We study various properties of this measure, including its connection with residual and past measures of discrepancy and interval entropy, and we obtain its upper and lower bounds. View Full-Text
Keywords: uncertainty; discrepancy; characterization uncertainty; discrepancy; characterization
This is an open access article distributed under the Creative Commons Attribution License (CC BY 3.0).

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Misagh, F.; Yari, G. Interval Entropy and Informative Distance. Entropy 2012, 14, 480-490.

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